Structural Equation Modeling with lavaan in R
Erin Buchanan
Professor
Degrees of Freedom (df)
Identification
#model specification
visual.model <- 'visual =~ x1 + x2 + x3 + x7 + x8 + x9'
#model analysis
visual.fit <- cfa(model = visual.model,
data = HolzingerSwineford1939)
summary(visual.fit)
lavaan (0.5-23.1097) converged normally after 27 iterations
Number of observations 301
Estimator ML
Minimum Function Test Statistic 106.553
Degrees of freedom 9
P-value (Chi-square) 0.000
Parameter Estimates:
Latent Variables:
Estimate Std.Err z-value P(>|z|)
visual =~
x1 1.000
x2 0.586 0.139 4.215 0.000
x3 0.882 0.149 5.923 0.000
x7 0.728 0.137 5.320 0.000
x8 0.944 0.143 6.599 0.000
x9 1.205 0.170 7.095 0.000
Variances:
Estimate Std.Err z-value P(>|z|)
.x1 0.973 0.093 10.405 0.000
.x2 1.249 0.106 11.789 0.000
.x3 0.975 0.090 10.842 0.000
.x7 0.979 0.087 11.311 0.000
.x8 0.678 0.069 9.841 0.000
.x9 0.455 0.069 6.580 0.000
visual 0.386 0.092 4.201 0.000
Structural Equation Modeling with lavaan in R